| xdiss {mvpart} | R Documentation |
The function computes extended dissimilarity indices which are for long gradients have better good rank-order relation with gradient separation and are thus efficient in community ordination with multidimensional scaling.
xdiss(data, dcrit = 1, dauto = TRUE, dinf = 0.5, method = "man",
use.min = TRUE, eps = 1e-04, replace.neg = TRUE, big = 10000,
sumry = TRUE, full = FALSE, sq = FALSE)
data |
Data matrix |
dcrit |
Dissimilarities < dcrit are considered to have no species in common
and are recalculated. |
dauto |
Automatically select tuning parameters – recommended. |
method |
Dissimilarity index |
use.min |
Minimum dissimilarity of pairs of distances used – recommended. |
dinf, eps, replace.neg, big |
Internal parameters – leave as is usually. |
sumry |
Print summary of extended dissimilarities? |
full |
Return the square dissimilarity matrix. |
sq |
Square the dissimilarities – useful for distance-based partitionong. |
The function knows the same dissimilarity indices as gdist.
Returns an object of class distance with attributes "Size" and "ok". "ok" is TRUE if rows are not disconnected (De'ath 1999).
Glenn De'ath
De'ath, G. (1999) Extended dissimilarity: a method of robust estimation of ecological distances from high beta diversity data. Plant Ecology 144(2):191-199.
Faith, D.P, Minchin, P.R. and Belbin, L. (1987) Compositional dissimilarity as a robust measure of ecological distance. Vegetatio 69, 57-68.
data(spider) spider.dist <- xdiss(spider)